In many modern technical infrastructures it is important to control the geographical position of one or more mobile units. For example, the mobile units may comprise autonomous or manually-controlled vehicles equipped with electronic positioning systems. The mobile units may be required to be present at a plurality of geographical positions over a given time period. For example, a fleet of autonomous vehicles may be required to perform number of actions at a number of different geographical positions. These positions may be tracked using the electronic positioning systems, for example based on measured geographic co-ordinates. Control systems may be arranged to monitor the movements of the mobile units to attempt to meet these requirements. For example, these control systems may be deterministic systems.
One problem faced by these control systems is uncertainty. The physical world is often unpredictable. For example, a mobile unit may be required to be present at a first geographical position at a first time and a second geographical position at a second time. The first geographical position may be a fixed distance from the second geographical position. A control system may thus calculate values for the first time and the second time based on a travel time for the fixed distance. However, due to uncertainty and unpredictability in the physical world, actual values for the times may differ from the calculated values. For example, times may vary based on, amongst others, one or more of: traffic, scheduled maintenance, weather, seasonal or periodic variations (e.g. based on start times and dates), physical conditions at each geographical position and complexity of equipment at each geographical position. Whereas most control systems are arranged to operate as linear deterministic systems, the reality of the physical world is often nonlinear and dynamic. Hence, it becomes difficult to control the geographical positions of the mobile units. This difficulty is then compound with further nonlinearities when controlling a plurality of mobile units wherein future geographical positions are based on a result at previous geographical positions.
WO2014/068314 A1 describes examples wherein a resource may be assigned a tour of tasks. Each of these tasks may have a geographical position. Assignment histories may be processed to determine estimated task durations. These estimated task durations may be used by a scheduling component to generate a schedule for a resource.